A novel approach is presented for automatic camera calibration from single images with three finite vanishing points in mutually or-thogonal directions (or of more independent images having two and/or three such vanishing points). Assuming ‘natural camera’, esti-mation of the three basic elements of interior orientation (camera constant, principal point location), along with the two coefficients of radial-symmetric lens distortion, is possible without any user interaction. First, image edges are extracted with sub-pixel accuracy, linked to segments and subjected to least-squares line-fitting. Next, these line segments are clustered into dominant space directions. In the vanishing point detection technique proposed here, the contribution of each image segment is calculated via a voting scheme, which involves the slope uncertainty of fitted lines to allow a unified treatment of long and short segments. After checking potential vanishing points against certain geometric criteria, the triplet having the highest score indicates the three dominant vanishing points. Coming to camera calibration, a main issue here is the simultaneous adjustment of image point observations for vanishing point esti-mation, radial distortion compensation and recovery of interior orientation in one single step. Thus, line-fitting from vanishing points along with estimation of lens distortion is combined with constraints relating vanishing points to camera parameters. Here, the prin-cipal point may be considered as the zero point of distortion and participate in both sets of equations as a common unknown. If a re-dundancy in vanishing points exists – e.g. when more independent images from the same camera with three, or even two, vanishing points are at hand and are to be combined for camera calibration – such a unified adjustment is undoubtedly advantageous. After the initial adjustment, the points of all segments are corrected for lens distortion to allow linking of collinear segments to longer entities, and the process is repeated. Data from automatic single-image calibrations are reported and evaluated against multi-image bundle ad-justment with satisfactory results. Finally, further interesting topics of study are indicated.